Title: 3D surface reconstruction of retinal vascular structures

Authors: Jihene Malek; Ahmad Taher Azar

Addresses: Electronics and Micro-Electronic Laboratory, Faculty of Sciences, Monastir University, Monastir, Tunisia ' Faculty of Computers and Information, Benha University, Egypt; Nanoelectronics Integrated Systems Center (NISC), Nile University, Egypt

Abstract: We propose in this paper, a three-dimensional surface reconstruction of a retinal vascular network from a pair of 2D retinal images. Our approach attempts to address the above challenges by incorporating an epipolar geometry estimation and adaptive surface modelling in a 3D reconstruction, using three steps: segmentation, 3D skeleton reconstruction and 3D surface modelling of vascular structures. The intrinsic calibration matrices are found via the solution of simplified Kruppa equations. A simple essential matrix based on a self-calibration method has been used for the fundus camera-eye system. The used method has eventually produced vessel surfaces that could be fit for various applications, such as applications for computational fluid dynamics simulations and applications for real-time virtual interventional.

Keywords: retinal vascular network; segmentation; self-calibration; Kruppa equations; epipolar geometry; 3D surface reconstruction; curvature-dependent subdivision; retinal images; modelling; fundus camera-eye systems; computational fluid dynamics; CFD; simulation.

DOI: 10.1504/IJMIC.2016.081131

International Journal of Modelling, Identification and Control, 2016 Vol.26 No.4, pp.303 - 316

Received: 14 Oct 2015
Accepted: 07 Nov 2015
Published online: 24 Dec 2016 *

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